Rank algorithms propose good solutions for image smoothing and impulse noise removing. In our previous work on the subject we have proposed methods for fast computations of εV and KNV neighborhood average based on multiscale histograms. In this paper a new method for multiscale histograms fast updating is described and analyzed. Performance comparisons of the combined methods with fastest known median filtering algorithm are given. We have achieved the processing speed for εV and KNV neighborhood average algorithms only a few times slowly than the fastest known median filtering algorithm.